Anxiety Disorder (GAD) is a pervasive and often chronic disorder affecting between 4% and 7% of the population. GAD is frequently comorbid with Major Depressive Disorder (MDD), with which lifetime diagnoses co-occur between 40% and 75% of the time. The present proposal aims to shed light on how GAD relates to error processing, as well as how depressive symptoms impact anxiety-related processes using the error-related negativity (ERN), a deflection in the event-related brain potential (ERP) subsequent to an erroneous response. A number of studies have reported increased ERNs in anxious and worried populations. However, no studies to date have examined the ERN in a clinical sample of GAD, nor has the influence of comorbid depression on error-related brain activity been systematically evaluated. In the present study, our working model is that although GAD will be related to an increased ERN, symptoms specific to depression will relate to a decreased ERN. We are testing the novel hypothesis that the presence of MDD may mask, or even alter, the relationship between GAD and an enhanced ERN. We will also explore mechanisms of this hypothesized relationship, thereby establishing the ERN as a neural measure that is sensitive to the interaction between Negative and Positive Affect. Consistent with the mission of the Division of Neuroscience and Basic Behavioral Science at the National Institute of Mental Health, the goal of this study is to examine neural correlates of error-monitoring in GAD and comorbid GAD/MDD using two direct measures of neural activity, ERPs and spectral analysis of the electroencephalogram (EEG). The proposed study has four specific aims: (a) to examine neural correlates of error-monitoring in individuals with GAD compared to controls; (b) to examine neural correlates of error-monitoring in individuals with comorbid MDD; (c) to explore relationships between the ERN and specific symptoms of each disorder; and (d) to examine these hypotheses using spectral analyses of error-related brain activity. One hundred and fifty adults (50 GAD, 50 comorbid GAD/MDD, and 50 control) will be recruited. Under the guidance of Dr. Hajcak, scalp-recorded ERPs and oscillatory EEG activity will be recorded during a laboratory task designed to elicit errors. We will derive response-locked ERPs, and complex wavelet decomposition will be used to perform spectral analysis of the EEG signal. Following this, source localization procedures will be used to identify potential neural generators. The current training proposal will allow the applicant to integrate training from co-mentors with expertise in ERN and anxiety (Dr. Hajcak), and models of comorbidity between anxiety and depression (Dr. Klein), as well as training from consultants with expertise in time-frequency analyses (Dr. Keil), and source localization of ERP/EEG signals (Dr. Pizzagalli).